The Wishtree Blog

Many enterprise AI projects have a clear beginning and a very visible launch.

Generative AI has officially moved to a frontline operational priority. In banking, healthcare, and insurance, models like Claude are already being put to work across claims, underwriting, documentation, and compliance.

Claude is only as useful as the data around it, and most data lakes weren't built for that. Here's how to structure context on AWS and Databricks without creating a…

The model-selection conversation often starts with the wrong question:

The first version of an enterprise copilot usually begins with a familiar request:

By now, almost every leadership team has said some version of the same thing:

Over the past year, enterprise engineering teams have rapidly transitioned from single-turn Retrieval-Augmented Generation (RAG) pipelines to background multi-agent orchestrations. Rather than simply answering single-turn user queries, autonomous agents plan…

For fintech and healthtech organizations, governance is not a “nice to have.” It is embedded in laws, supervisory expectations, and customer trust. Financial institutions must prove who accessed which transaction…

Every business wants real‑time intelligence. In fintech, fraud needs to be stopped before authorization completes. In adtech, bids must be priced in milliseconds. In supply chains, routing decisions have to…

Most teams adopting Databricks expect a “data and AI reset button.” Leadership sees Unity Catalog on the roadmap and assumes it will finally unify access, governance, and AI across ERP,…

Most enterprise AI initiatives begin with an impressive demo. A developer hooks a hosted SaaS model API up to an internal document store over a weekend.

Across the industry, AI budgets are growing fast. Finance teams are approving significant spend on: